The University of Florida is seeking companies interested in commercializing a data structure system for measuring network traffic and storing network contact information in a small memory space. Every day, businesses and individuals are bombarded with everything from spam e-mail to corporate hackers. As networks have gotten faster and information transfer has greatly increased, measuring network traffic has become progressively more important for allocating network resources and ensuring security. In order to measure and track what is entering and leaving your network, it is necessary to contain vast amounts of information in a compact memory space. Unfortunately, today’s traffic far exceeds the capabilities of any system currently available. Researchers at the University of Florida have developed a new spread estimator that delivers excellent performance in a tight memory space where all existing estimators no longer work. Not only does it achieve space compactness, but it also operates more efficiently than existing systems.
Network traffic management systems and network security systems
- Performs exceptionally under small memory constraints, providing a more efficient and reliable means of measuring network traffic
- Continues to collect valuable data where all other systems no longer work, creating a competitive advantage
- Able to measure and remove all errors in spread estimation, providing an accurate route for data storage
- Utilizes an advanced memory system, allowing for complex data storage and spread estimation on high-speed routers
A spread estimator is a software/hardware module on a router that inspects the arrival packets and estimates the spread of each source. The spread is defined as the number of distinct internal hosts that an external host (called a source) has contacted during a measurement period. It has important applications in detecting port scans and distributed denial of service attacks, measuring the infection rate of a worm, assisting resource allocation in a server farm, determining popular web contents for caching, and much more. The main technical challenge is to fit a spread estimator in a fast but small and expensive cache memory in order to operate it at the line speed in a high-speed network. In this invention, researchers at the University of Florida have designed a new spread estimator that delivers good performance in tight memory space where all existing estimators no longer work. The estimator effectively achieves space compactness and also operates more efficiently than anything available on the market today. Its accuracy and efficiency come from a new structure for data storage, called virtual vectors, which allow for the measurement and removal of errors in spread estimation.